Better prediction of extreme winds at sparsely observed locations could help optimize the design of wind farms.
Factors influencing the tolerance of barley to saline soils have been uncovered using an advanced robust statistical technique.
Ajay Jasra is a professor of applied mathematics and computational sciences who recently joined the KAUST CEMSE Division in July 2019.
New methods for training machine learning models are quicker and more accurate than current approaches, previously considered state-of-the-art.
David Bolin is an associate professor of mathematical statistics who joined the KAUST Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division earlier this month from the Department of Mathematical Sciences at the University of Gothenburg.
Before joining KAUST, Bolin received both his Ph.D. degree in mathematical statistics and M.S.c in engineering mathematics from Lund University, Sweden, in 2012 and 2007, respectively. Upon completing his Ph.D., he spent one year at Umeå University, Sweden, working as a postdoctoral fellow before moving to the Chalmers University of Technology. In 2016, Bolin became an associate professor of mathematics at the University of Gothenburg, where a year later he received the title of Docent in mathematical statistics.
Joaquín Ortega Sánchez is an instructional professor of statistics who joins the KAUST CEMSE Division after spending the last sixteen years working at the Mathematics Research Center (CIMAT) in Guanajuato, Mexico. Born in Venezuela, Ortega completed his postgraduate and graduate studies in London, where he studied mathematics at King’s College London, before obtaining his Ph.D. in Probability Theory across the city at Imperial College London. After his time in the U.K., he returned to his native Venezuela where he worked for over 20 years at the Universidad Central de Venezuela, Caracas.
Over the course of his career, Ortega’s research work has focused on stochastic processes, specifically Gaussian processes and time series with applications in oceanography and biostatistics. And more recently his work has focused on functional data analysis.
A deep learning tool could help in structure-based drug discovery.
Areas without earthquake monitoring systems could model the tremors by using data from local landslides.
Deep analysis of the way information is shared among parallel computations increases efficiency to accelerate machine learning at scale.
Mohamed Eddaoudi, KAUST distinguished professor of chemical science and director of the University's Advanced Membrane & Porous Materials Center, recently received the Abdul Hameed Shoman Award for Arab Researchers for Renewable Energy, an award presented annually by the Abdul Hameed Shoman Foundation.
Omar Knio, KAUST professor of applied mathematics and computational science, was also honored by the Abdul Hameed Shoman Foundation this year as a joint recipient of the Shoman Award for Mathematical Modeling with Dr. Shaher Mohammed Ahmad Momani.
The 3 faculty positions are in the Statistics Program (http://stat.kaust.edu.sa) within the Computer, Electrical, and Mathematical Sciences and Engineering Division. Currently, the Statistics Program has 7 core faculty and 10 affiliated faculty. We are primarily interested in applicants with strong background in one of the following areas: (1) Statistical Data Science and AI, including network data analysis and high-dimensional statistics (https://apply.interfolio.com/69165); (2) Statistical Climatology, with expertise in statistical analysis of climate model output data, in particular regional climate models, and in physical systems (https://apply.interfolio.com/69167); (3) Statistics for Public Health, including smart health data analysis, personalized medicine, and disease mapping (https://apply.interfolio.com/69168).
A more accurate and efficient method of capturing the local factors that lead to extreme rainfall enables better flood prediction across larger regions.
Ghulam Qadir, a third-year Ph.D. student in KAUST Associate Professor Ying Sun's Environmental Statistics research group, recently received a best poster award from the Italian Environmetrics Society (GRASPA) and the International Environmetrics Society (TIES) at the GRASPA 2019 conference held from July 15 to 16 in Pescara, Italy.
More accurate detection of hotspot clusters provides new insights into the behavior of air pollution.
Peter Richtárik, KAUST professor of computer science, recently received a Distinguished Speaker Award at the Sixth International Conference on Continuous Optimization (ICCOPT 2019) held in Berlin from August 3 to 8. ICCOPT 2019 was organized by the Mathematical Optimization Society and was hosted this year by the Weierstrass Institute for Applied Analysis and Stochastics.